New Beam Tracking Technique for Millimeter Wave-band Communications
(2017)

In this paper, we propose an efficient beam tracking method for mobility scenario in mmWave-band communications. When the position of the mobile changes in mobility scenario , the base-station needs to perform beam training frequently to t rack the time-varying channel, thereby spending significant res ources for training beams. In order to reduce the training overhead, we propose a new beam training approach called “beam tracking” which exploits the continuous nature of time varying angle of departure (AoD) for beam selection. We show that transmissi on of only two training beams is enough to track the time-varying AoD at good accuracy. We derive the optimal selection of beam pai r which minimizes Cramer-Rao Lower Bound (CRLB) for AoD estimation averaged over statistical distribution of the AoD. Our numerical results demonstrate that the proposed beam track ing scheme produces better AoD estimation than the conventiona l beam training protocol with less training overhead. I. I NTRODUCTION The next generation wireless communication systems aim to achieve Giga bit/s throughput to support high speed multimedia data service [1], [2]. Since there exist ample amount of unutilized frequency spectrum in millimeter Wave (mmWave) band (30 GHz-300 GHz), wireless communication over mmWave band is considered as a promising solution to achieve significant leap in spectral efficiency [3]. However , one major limitation of mmWave communications is significant free space path loss, which causes large attenuation of sign al power at the receiver. Furthermore, the overall path loss ge t worse when the signal goes through obstacles, rain, foliage , and any blockage to mobile devices. Recently, active resear ch on mmWave communication has been conducted in order to overcome these limitations [1]–[5]. In mmWave band, many antenna elements can be integrated in a small form factor and hence, we can employ high directional beamforming using a large number of antennas to compensate high path loss. In order to perform high directional beamforming, it is necessary to estimate channels for all transmitter and rece iver antenna pair. While this step requires high computational c omplexity due to large number of antennas, channel estimation can be performed efficiently by using the angular domain representation of channels [6]. In angular domain, only a fe w angular bins contain the most of the received energy. Hence, if we identify the dominant angular bins (which correspond to the angle of arrival (AoA) and the angle of departure (AoD)), we can obtain the channel estimate without incurrin g computational complexity. Basically, both AoD and AoA can be estimated using so called “beam training” procedure. The base-station sends t he training beams at the designated direction and the receiver estimates the AoD/AoA based on the received signals. Widely used beam training method (called “beam cycling method”) is to allow the base-station to transmit N training beams one by one at the equally spaced directions. However, to ensure good estimate of AoD/AoA, N should be large, leading to significant training overhead. This problem becomes even more serious for the mobility scenario in mmWave communications. Since the location of mobiles keeps changing, th e base-station should transmit training beams more frequent ly to update AoD/AoA estimates, causing significant drop in data throughput [7]. Recently, several adaptive beam train ing schemes have been proposed to improve the conventional beam training method [10]–[14]. In this paper, we introduce a novel beam training method for mobility scenario in mmWave communications. Our idea is based on the observation that for mobility scenario, the AoD of the particular user does not change drastically so that continuous nature of the AoD change can be accounted to improve the efficacy of the beam training. Since this approach exploits temporal dynamics of AoD, we call such beam training scheme “beam tracking”. While the convenional method makes no assumption on the state of AoD, we use statistical distribution of the AoD given the previousl y state of AoD. Using the probabilistic model on AoD change, we derive effective beam tracking strategy which employs transmission of two training beams from the base-station. Optimal placement of two training beams in angular domain is sought by minimizing (the lower bound of) variance of the estimation error for AoD. As a result, we choose the best beam p ir from the beam codebook for the given prior knowledge on AoD. Our simulation results show that the proposed beam tracking method offers the channel estimation performance comparable to the conventional beam training methods with significantly reduced training overhead. The rest of this paper is organized as follows; In section II, we introduce the system and channel models for mmWave communications and in section III, we describe the proposed b am tracking method and the simulation results are provide d in section IV. Finally, the paper is concluded in section V. II. SYSTEM MODEL In this section, we describe the system model for mmWave communications. First, we describe the angular domain repr esentation of the mmWave channel and then we introduce the procedure for beam training and channel estimation. A. Channel Model Consider single user mmWave MIMO systems with the base-station withNb antennas and the mobile with Nm antennas. The MIMO channel model with L paths at timet is described by [8]